Robust Asymptotical Stability and Stabilization of Fractional-Order Complex-Valued Neural Networks with Delay. (15th November 2021)

• Record Type: Journal Article
• Authors: Zeng, Jingjing; Yang, Xujun; Wang, Lu; Chen, Xiaofeng
• Other Names: Pawluszewicz Ewa Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2021(2021)
• Publication Date: 2021-11-15
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2021/5653791
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : The robust asymptotical stability and stabilization for a class of fractional-order complex-valued neural networks (FCNNs) with parametric uncertainties and time delay are considered in this paper. It is worth noting that our system combines complex numbers, uncertain parameters, time delay, and fractional orders, which is universal in practical application. Using the theorem of homeomorphism, the sufficient condition of the existence and uniqueness of the equilibrium point for the system is obtained. Then, the sufficient criteria of robust asymptotical stability and stabilization for the addressed models are established, respectively. Finally, we give two numerical examples to verify the feasibility and effectiveness of the theoretical results.